grid control cooperation – coordination of secondary control · coordination of secondary...

Prof. Dr. techn. G. Scheffknecht

Institute of Combustion and Power Plant Technology

Exchange of balancing services ‐ Market design and modelling, AmsterdamOctober 28, 2010

Dipl.-Ing. Pavel ZolotarevUniversity of Stuttgart

Grid Control Cooperation –

Coordination of Secondary Control

Introduction

Continental Europe power system - synchronously interconnected control areas

Load and power generation from renewable sources cannot be predicted accurately.

In order to ensure the power system stability power generation must be continuously adjusted to power demand by load-frequency control.

Introduction

Continental Europe power system - synchronously interconnected control areas

Load and power generation from renewable sources cannot be predicted accurately.

In order to ensure the power system stability power generation must be continuously adjusted to power demand by load-frequency control.

Secondary Control (SC):• Stationary restores the power balance of a control area • Control variable – actual power interchange of a control area• Horizontal structure:

− One controller implemented in each control area− No coordination of secondary control power (SCP) activation

Secondary Control Loop

Power balance of a control area

Control deviation: Area Control Error (ACE)

Power Balance

Control area short – positive SCP demandControl area long – negative SCP demand

Secondary Controller

Power Balance

SCP-request

SC Power Plant Units

Power Balance

SCP-request

Dimensioning of necessary SCP reserves and their activation is conducted with respect to technical and economic criteria for one

control area!

Power Balance

SCP-request

Interconnected Power System

Power Balance

SCP-request

Control Area A

Power Balance

SCP-request

Control Area A

Power Balance

SCP-request

Control Area C

Power Balance

SCP-request

Control Area B

other control areas

Technical and financial benefit through Grid Control Cooperation!

1. Grid Control Cooperation Modules

2. Technical Concept

3. Example from Operation

4. Implementation in Germany

5. Summary

Module 1

Module 1:

Inherent in the system: concurrently short and long control areas activate SCP with different signs.

Counteracting SCP avoidance

Less control energy needed (lower energy costs)

Grid Control Cooperation

Module 2

Module 2:

Control areas must cover the risk of power imbalances with SCP reserves.

Risk distribution and joint dimensioning of SCP reserves

Lower SCP reserves needed (lower costs)

Module 1:Counteracting SCP avoidance

Module 3

Module 3:

SCP reserves must be procured.

Joint cross-border procurement

Overall cheapest SCP is bought

Higher supply but stable demand could lead to lower prices

Module 2:Joint dimensioning of SCP reserves

Module 4

Module 4:

SCP is activated under consideration of energy costs (e.g. with respect to a merit order list).

Cross-border cost optimal SCP activation

Possible market based effects on control energy price

Module 3:Joint SCP procurement

Grid Control Cooperation Modules

Module 4:Cross-border cost-optimal SCP activation

5. Summary and Outlook

Module 3:Joint SCP procurementonly organizational

Power Balance

SCP-request

Control Area A

Power Balance

SCP-request

Control Area C

Power Balance

SCP-request

Control Area B

other control areas

Technical and financial benefit through Grid Control Cooperation!

Secondary Control Optimization

Power Balance

SCP-request

Control Area A

Power Balance

SCP-request

Control Area C

Power Balance

SCP-request

Control Area B

other control areas

SC-Optimization

correction

SCP demand SCP demand

Integration into Secondary Control Structure

int,aP -

K f∆int,setP Secondary Controller Secondary ControlledPower Plant Units

sc,setP-ACEP

existing

distint,aP

int,aP -

sc,setP-ACEP

existing

corr,2 corr,3 corr,, , , iP P P

SC-Optimization

corr,1P

int,aP

sc,setPACEP

existing

newdemand,1P

demand,2 demand,3 demand,, , , iP P P

sc,aP-

SC-Optimization

corr,1P

int,aP

sc,setPACEP

existing

newdemand,1P

Definition of SCP demand?

SC-Optimization

corr,1P

int,aP

sc,setPACEP

-ACE corr,1P P−

existing

newdemand,1P

Demand = ACE without correction

SC-Optimization

corr,1P

int,aP

sc,setPACEP

-ACE corr,1P P− sc,aP

existing

newdemand,1P

Demand = ACE without correction and without activated SCP

SC-Optimization

corr,1P

int,aP

sc,setPACEP

existing

newdemand,1P

distint,aP

SC-Optimization

corr,1P

int,aP

sc,setPACEP

existing

newdemand,1P

distint,aP

Demand contains no information fromclosed control loop –

Stability is guaranteed!

SC-Optimization

corr,1P

int,aP

sc,setPACEP

existing

newdemand,1P

import/export boundson/off switch

Grid Control Cooperation in Germany

Four control areas• Amprion GmbH (AMP)• TenneT TSO GmbH (TTG)• 50Hertz Transmission GmbH (50Hz)• EnBW Transportnetze AG (TNG)

50HzTTG

December 2008: Grid Control Cooperation launched by TNG,

50Hz and TTG Control areas remain independent

University of Stuttgart

Example from Operation

0 5 10 15 20 25 30 35 40 45 50 55 60-400

SCP demands

TNG demand 50Hz demand TTG demand

0 5 10 15 20 25 30 35 40 45 50 55 60-400

Counteracting SCP Demands

SCP demands counteracting counteractingcounteractingcounteracting

TNG demand 50Hz demand TTG demand

Netted Demand

Netted SCP demand of all participants

0 5 10 15 20 25 30 35 40 45 50 55 60600

+ 1500 MW

+ 640 MW

GCC demand

TNG Demand

0 5 10 15 20 25 30 35 40 45 50 55 60-200

TNG demand

0 5 10 15 20 25 30 35 40 45 50 55 60-200

TNG demand TNG Module 1

0 5 10 15 20 25 30 35 40 45 50 55 60-200

Saved energy!

0 5 10 15 20 25 30 35 40 45 50 55 60-200

Cross-border cost optimization?

Goal: Cost Optimal Netted Demand Coverage

0 5 10 15 20 25 30 35 40 45 50 55 60600

+ 1500 MW

+ 640 MW

GCC demand

Cost optimization only for positive SCP demand needed

Positive Merit Order List

+ 640 MW

+ 1500 MW

Merit Order List Position

Available in TNG [MW]

Available in TTG [MW]

Available in 50Hz [MW]

Available in Total [MW]

1 20 0 0 20

2 0 55 0 75

3 40 0 0 115

4 0 160 0 275

5 160 0 0 435

6 0 35 0 470

7 320 0 0 790

8 0 0 433 1223

9 428 0 0 1651

(minimum demand)

(maximum demand)

Lowest energy price

Highest energy price

Positive Merit Order List

Coverage of minimum SCP demand (always activated)

Coverage of maximum SCP demand

Merit Order List Position

Available in TNG [MW]

Available in TTG [MW]

Available in 50Hz [MW]

Available in Total [MW]

1 20 0 0 20

2 0 55 0 75

3 40 0 0 115

4 0 160 0 275

5 160 0 0 435

6 0 35 0 470

7 320 0 0 790

8 0 0 433 1223

9 428 0 0 1651

+ 640 MW

+ 1500 MW

(minimum demand)

(maximum demand)

Lowest energy price

Highest energy price

TNG Demand and Module 1

0 5 10 15 20 25 30 35 40 45 50 55 60-200

TNG Module 1 and Module 4

0 5 10 15 20 25 30 35 40 45 50 55 60-200

SCP demand, Module 1 and Module 4 correction signals

TNG demand TNG Module 1 TNG Module 4

0 5 10 15 20 25 30 35 40 45 50 55 60-200

TNG – Effect of Correction Signal

TNG demand

SCP demand, correction signals and demand after correction

TNG Module 1 TNG Module 4 TNG corrected demand

50Hz – Effect of Correction Signal

50Hz demand 50Hz corrected demand

SCP demand and demand after correction

0 5 10 15 20 25 30 35 40 45 50 55 60-200

TTG – Effect of Correction Signal

SCP demand and demand after correction

TTG demand TTG corrected demand

0 5 10 15 20 25 30 35 40 45 50 55 600

Goal: Cost Optimal Netted Demand Coverage

0 5 10 15 20 25 30 35 40 45 50 55 60600

+ 1500 MW

+ 640 MW

GCC demand

Result of Grid Control Cooperation

Netted SCP demand of all participants and sum of secondary controller outputs

0 5 10 15 20 25 30 35 40 45 50 55 60600

1600MW

GCC demand Sum of secondary controller outputs

The sum of SCP activation = Netted GCC demand!

50HzTTG

May 2010: AMP joins the Grid Control Cooperation

50HzTTG

Timeline of Implementation

Nov. Dec. Jan. Feb. Mar. Apr. May. Jun. Jul. Aug. Sep. Oct.

20092008

Module 1 Module 2 Module 3 Module 4

Module 1: Counteracting SCP avoidance (December 2008)

Common balancing energy price for participating control areas (May 2009)

Module 2: Joint dimensioning of SCP reserves (June 2009)

Module 3: Joint procurement (July 2009)

Module 4: Cross-border cost optimization (October 2009)

Common balancing energy price

Estimated Cost Savings for Germany

20092008

Module 1 Module 2 Module 3 Module 4

Module 1: Counteracting SCP avoidance (December 2008) – approx. 120 mil. € pa.

Common balancing energy price for participating control areas (May 2009)

Module 2: Joint dimensioning of SCP reserves (June 2009) – approx. 140 mil. € pa.

Module 3: Joint procurement (July 2009)

Module 4: Cross-border cost optimization (October 2009)

Common balancing energy price

double digit mil. € savings

3. Modelling

5. Summary

Summary

Grid Control Cooperation:• Counteracting SCP avoidance (Module 1)• Joint dimensioning of SCP reserves (Module 2)• Joint SCP procurement (Module 3)• Cross-border cost-optimal SCP activation (Module 4)

Summary

Coordination of secondary control while maintaining the independence of participating control areas and power system stability

Congestion management system allows restriction power interchange within the Grid Control Cooperation framework

Summary

Coordination of secondary control while maintaining the independence of participating control areas and power system stability

Congestion management system allows restriction power interchange within the Grid Control Cooperation framework

Implementation in Germany:• Cost savings: approximately 300 mil. € pa.• Common balancing energy price• Harmonization of SCP market

The End

Thank you!

# Simplicity# Stability# Back-up plan# Cost savings# Market impact# Extension

VE-TTPS

Stuttgart

20092008

Module 1 Module 2 Module 3 Module 4Common balancing energy price

Module 4:Cost-optimal SCP activation

SecondaryController

Power Balance

SCP-request

Control Area A

Power Balance

SecondaryController

SCP-request

Control Area C

SecondaryController

Power Balance

SCP-request

Control Area B

other control areas

SC-Optimization

correction

demand demand

Powergrid 08.06.2010

SC-Optimization

corr,1P

int,aP

sc,setPACEP

existing

newdemand,1P

import/export boundson/off switch

scheduled power plant units

secondary controller

secondary controlled power plant units

schedule

- primary controlled power plants and

self-regulating effect

ΣK f∆

int,setP

sc,setP

demandPcorrP

2,schedP

1,schedP

−load genP P

3,schedP

int,aP

Modelling of Power Systems at IFK

12oE 24oE

54 oN Nonlinear, dynamic model of the ENTSO-E CE power system including: > 1000 power plant units > 3000 dynamic loads > 7000 transmission lines > 900 transformers Investigation of dynamic and stationary power

system behavior 400 kV 220 kV HDVC

Wide Area Monitoring: 8 frequency measuring units in Europe:

• Sevilla, Madrid, Aalborg, Gliwice, Zagreb, Timisoara, Athens and Stuttgart

2 frequency measuring units in Africa:• Algiers/Algeria + Sfax/Tunesia

19 frequency measuring units in Turkey

Summary Dynamic Load-Frequency Model

Control Area 1

Control Area n

Control Area 2

Control Area k

Summary dynamic load-frequency behavior of a synchronous network:

……

Control Area 1

Control Area n

Control Area 2

Control Area k

−load genP P

……

Control Area 1

Control Area n

Control Area 2

Control Area k

Summarized Network

Dynamics

−load genP P

……

Control Area 1

Control Area n

Control Area 2

Control Area k

SC-Optimization

Summarized Network

Dynamics

demand corr,P P

……

−load genP P

Control Area Model

schedule

Control Area Model

Σschedule

2,schedP

1,schedP

3,schedP

primary controlled power plants and

Control Area Model

Σschedule

2,schedP

1,schedP

−load genP P

3,schedP

Control Area Model

Σschedule

2,schedP

1,schedP

−load genP P

3,schedP

Control Area Model

Σschedule

-Σf∆

2,schedP

1,schedP

−load genP P

3,schedP

Control Area Model

Σschedule

-Σf∆

sc,setPACEP

2,schedP

1,schedP

−load genP P

3,schedP

int,aP

K f∆

int,setP

Control Area Model

schedule

sc,setP

demandPcorrP

2,schedP

1,schedP

−load genP P

3,schedP

int,aP

K f∆

int,setP

Control Area Model

schedule

Σint,setP

sc,setP

demandPcorrP

2,schedP

1,schedP

−load genP P

3,schedP

int,aP

control area disturbance from measurements

K f∆

Remarks

Control area model can be used to represent a balancing group

Dynamic power plant models:• linear approximations for input-output behavior (“TSO perspective”),• or detailed, nonlinear models for investigations of load-frequency control impact on

power plant units (“power plant perspective”)− different power plant types (coal-fired, hydraulic, nuclear etc.)− different operating modes (turbine in control, steam generator in control)

Simplifications with respect to the focus of investigations are possible

Remarks

Control area model can be used to represent a balancing group

Dynamic power plant models:• linear approximations for input-output behavior (“TSO perspective”),• or detailed, nonlinear models for investigations of load-frequency control impact on

power plant units (“power plant perspective”)− different power plant types (coal-fired, hydraulic, nuclear etc.)− different operating modes (turbine in control, steam generator in control)

Simplifications with respect to the focus of investigations are possible

Model validation based on comparison of simulated and published secondary control energy and costs:

• Simulation tends to overestimate activated control energy (and thus costs)• Overestimation error is smaller than 10%

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